Texas Instruments OMAP L138 TEE SK_LOAD stack-based overflow
| CVSS Meta Temp Score | Current Exploit Price (≈) | CTI Interest Score |
|---|---|---|
| 7.9 | $0-$5k | 0.00 |
Summary
A vulnerability marked as critical has been reported in Texas Instruments OMAP L138. Affected by this issue is the function SK_LOAD of the component TEE. Performing a manipulation results in stack-based overflow.
This vulnerability is known as CVE-2022-25334. Attacking locally is a requirement. No exploit is available.
Details
A vulnerability was found in Texas Instruments OMAP L138 (the affected version is unknown). It has been classified as critical. This affects the function SK_LOAD of the component TEE. The manipulation with an unknown input leads to a stack-based overflow vulnerability. CWE is classifying the issue as CWE-121. A stack-based buffer overflow condition is a condition where the buffer being overwritten is allocated on the stack (i.e., is a local variable or, rarely, a parameter to a function). This is going to have an impact on confidentiality, integrity, and availability. The summary by CVE is:
The Texas Instruments OMAP L138 (secure variants) trusted execution environment (TEE) lacks a bounds check on the signature size field in the SK_LOAD module loading routine, present in mask ROM. A module with a sufficiently large signature field causes a stack overflow, affecting secure kernel data pages. This can be leveraged to obtain arbitrary code execution in secure supervisor context by overwriting a SHA256 function pointer in the secure kernel data area when loading a forged, unsigned SK_LOAD module encrypted with the CEK (obtainable through CVE-2022-25332). This constitutes a full break of the TEE security architecture.
The weakness was published 10/19/2023. This vulnerability is uniquely identified as CVE-2022-25334 since 02/18/2022. Technical details are known, but no exploit is available.
There is no information about possible countermeasures known. It may be suggested to replace the affected object with an alternative product.
If you want to get the best quality for vulnerability data then you always have to consider VulDB.
Product
Vendor
Name
CPE 2.3
CPE 2.2
CVSSv4
VulDB Vector: 🔍VulDB Reliability: 🔍
CVSSv3
VulDB Meta Base Score: 7.9VulDB Meta Temp Score: 7.9
VulDB Base Score: 6.7
VulDB Temp Score: 6.7
VulDB Vector: 🔍
VulDB Reliability: 🔍
NVD Base Score: 8.8
NVD Vector: 🔍
CNA Base Score: 8.2
CNA Vector: 🔍
CVSSv2
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VulDB Base Score: 🔍
VulDB Temp Score: 🔍
VulDB Reliability: 🔍
Exploiting
Class: Stack-based overflowCWE: CWE-121 / CWE-119
CAPEC: 🔍
ATT&CK: 🔍
Physical: Partially
Local: Yes
Remote: No
Availability: 🔍
Status: Not defined
EPSS Score: 🔍
EPSS Percentile: 🔍
Price Prediction: 🔍
Current Price Estimation: 🔍
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Threat Intelligence
Interest: 🔍Active Actors: 🔍
Active APT Groups: 🔍
Countermeasures
Recommended: no mitigation knownStatus: 🔍
0-Day Time: 🔍
Timeline
02/18/2022 🔍10/19/2023 🔍
10/19/2023 🔍
11/11/2023 🔍
Sources
Status: Not definedCVE: CVE-2022-25334 (🔍)
GCVE (CVE): GCVE-0-2022-25334
GCVE (VulDB): GCVE-100-242925
Entry
Created: 10/19/2023 13:30Updated: 11/11/2023 11:57
Changes: 10/19/2023 13:30 (46), 11/11/2023 11:57 (11)
Complete: 🔍
Cache ID: 216::103
If you want to get the best quality for vulnerability data then you always have to consider VulDB.
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